Design and Test of an Autonomy Monitoring Service to Detect Divergent Behaviors on Unmanned Aerial Systems
Abstract
Operation of Unmanned Aerial Vehicles (UAV) support many critical missions in the United State Air Force(USAF). Monitoring abnormal behavior is one of many responsibilities of the operator during a mission. Somebehaviors are hard to be detect by an operator, especially when flying one or more autonomous vehicles; as such,detections require a high level of attention and focus to flight parameters. In this research, a monitoring system andits algorithm are designed and tested for a target fixed-wing UAV. The Autonomy Monitoring Service (AMS)compares the real vehicle or simulated Vehicle with a similar simulated vehicle using Software in the Loop (SITL).It is hypothesized that the resulting design has the potential to reduce monotonous monitoring, reduce risk of losingvehicles, and increase mission effectiveness. Performance of the prototyped AMS model was examined by severalmeasures, including divergence detection rate, synchronization time, and Upper Control Limit (UCL) of aircraftlocation variability in different scenarios. Results showed 100 rate of divergence detection out of all divergentevents occurred. The weighted mean of AMS synchronization time was 4.02 seconds, and the weighted mean foraircraft location variability was 44.8 meters. The overarching AMS functionality was achieved. AMS supports theconcept that humans and machines should be designed to complement each other by sharing responsibilities andbehaviors effectively, making final system safer and more reliable.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 2020
- Accession Number
- AD1107616
Entities
People
- Loay Y. Almannaei
Organizations
- Air Force Institute of Technology